Federato vs Kalepa (2026)
The cleanest question in this pairing is whether the machine ever decides. Federato says yes and describes exactly when: the system drafts the best triaged deals and explains its reasoning while the underwriter adjusts and owns the relationship, a defined subset of deals that clearly fit strategy is fully executed by the AI under predefined rules and guardrails, and those automated decisions are randomly audited by underwriters for quality control. Naming which decisions are automated, what constrains them and what the sampling control is, in public, is what almost every other vendor leaves implicit, and this index treats it as the reference point for the axis. Kalepa says no and draws the line just as narrowly: Copilot reads, cross references and scores, the underwriter decides, with the reasoning behind every flag visible. Both earn A on oversight for opposite reasons, which is the point. The second split is architectural and equally deliberate. Federato takes A on integration depth by sitting on top of the policy administration core with native connections to the three dominant platforms in this market, replacing the underwriter desktop rather than the system of record, on an eight to twelve week implementation. Kalepa takes C by design, working on day one with no integrations at all.
- You want a defined subset of deals to execute without an underwriter. Clearly on strategy deals are fully executed by the system under predefined rules and guardrails, with random underwriter audit sampling behind them, the most explicit published autonomy design in this index.
- The platform has to live with your core. Native interface integrations reach the three dominant policy administration platforms, so the product replaces the underwriter desktop while leaving the system of record in place, covering submission intake, pricing, quoting, documentation and referral workflow through to invoice.
- Portfolio position drives your selection. Real time exposure and accumulation analysis sits alongside submission triage against stated appetite, so a risk is judged against the book rather than on its own merits.
- Your reinsurers are part of the argument. The platform produces audit ready evidence of appetite adherence and referral activity that carriers present to reinsurers, which puts a capital provider with its own money at risk in the position of scrutinising the discipline the system enforces.
- The underwriter must remain the decision maker. The division of labour is stated narrowly and holds throughout: Copilot reads, cross references and scores, the underwriter decides, and no subset of deals is executed automatically.
- You cannot wait a quarter to see value. Copilot works out of the box on day one with no integrations, with inbox, portal and policy system connections available afterwards, against an eight to twelve week implementation at the alternative.
- The submission is only half the risk. Copilot cross references billions of data points from loss runs, web sources and third party providers to surface exposures the submission did not mention, rather than triaging what the broker chose to disclose.
- Nothing sellable should survive removing the AI. Kalepa takes A on centrality because the product had no existence before the models, where the alternative sits at B: strip its models and a unified underwriting workflow with portfolio visibility remains, which is a substantial product in its own right.
This comparison is published by AI FinTech Index, an independent research platform that publishes independent ratings of AI vendors for financial services. Federato and Kalepa are each graded against the same capability taxonomy, from each vendor's own public materials and the regulatory record, under the AI FinTech Index verification standard. No vendor pays for placement, and no vendor has reviewed this page. How this evidence is graded
Plain facts
| Federato | Kalepa | |
|---|---|---|
| Primary category | Insurance AI | Insurance AI |
| Founded | Not published | 2018 |
| Headquarters | Not published | New York, New York, United States |
| Website | www.federato.ai | www.kalepa.com |
Side by Side
| Axis | F Federato |
K Kalepa |
|---|---|---|
| AI Centrality | ||
| Autonomy and Oversight Model | ||
| Model Risk Management and Transparency | ||
| Operational and Outcome Evidence | ||
| AI Safety and Data Stewardship | ||
| GLBA and Data Privacy Posture | ||
| Security Certifications and Trust Center | ||
| Regulatory Status and Licensure | ||
| AI Governance and Bias Disclosure | ||
| AI Liability and Recourse | ||
| Model Supply Chain Disclosure | ||
| Core Systems and Integration Depth | ||
| Deployment Model and Data Residency | ||
| Commercial Transparency | ||
| Institution and Segment Coverage |
The short version of each
Federato
Federato sells an underwriting platform for property and casualty carriers, managing general agents and mutuals that replaces the underwriter desktop while sitting on top of the existing policy administration core, triaging submissions against stated appetite, surfacing real time portfolio exposure and accumulation, drafting quotes with reasoning shown, and executing a defined subset of clearly on strategy deals automatically under preset guardrails with underwriter audit sampling behind it. The AI FinTech Index treats its published autonomy design as the reference point for that axis, naming which decisions are automated, what constrains them and what the sampling control is, and records A grades on integration depth for native connections to the three dominant policy administration platforms and on outcome evidence for named executives and falsifiable hit ratio claims. The index records the gaps: no model provider, external data source or subprocessor identified anywhere, and no testing for unfair discrimination described against a state framework whose obligations land on the carrier.
Source: AI FinTech Index, 2026
Kalepa
Kalepa builds Copilot, an underwriting workbench for commercial and specialty property and casualty insurers that reads a submission on arrival, cross references billions of data points from loss runs, web and third party sources, surfaces exposures the submission did not mention and prioritises risks by likelihood to bind and fit against carrier appetite, with independent judging agents validating critical fields and a stated division of labour where Copilot scores and the underwriter decides. The AI FinTech Index records it at A on AI centrality, since the product had no existence before the models, and at A on oversight and outcome evidence, with named users spanning Munich Re Specialty, Bowhead and SECURA. The index records the gaps: integration depth traded away by design with no policy administration platform named, a market leading accuracy claim carrying no figure, named carriers and quantified results that never attach to the same account, and crime and legal action data used as underwriting exposure with no fairness testing published.
Source: AI FinTech Index, 2026
Common questions
Is Federato better than Kalepa for property and casualty underwriting?
They answer different questions about who decides. Federato executes a defined subset of clearly on strategy deals automatically under guardrails with random underwriter audit, and sits on top of the policy administration core with native connections to the three dominant platforms. Kalepa never automates the decision, stating that Copilot scores and the underwriter decides, and works on day one with no integrations. Both take A on oversight and on outcome evidence. Federato takes A on integration depth where Kalepa takes C by design; Kalepa takes A on AI centrality where Federato takes B. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified September 5, 2026. No vendor pays for placement.
Which one actually automates underwriting decisions?
Federato, within a stated boundary. It names three distinct modes rather than gesturing at human in the loop: the system drafts the best triaged deals and shows its reasoning while the underwriter adjusts, a defined subset that clearly fits strategy is fully executed under predefined rules and guardrails, and those automated decisions are randomly audited by underwriters for quality control. Kalepa automates no decision. Its ensemble engine decides where to automate rather than assist within the analysis, but the bind decision stays with the underwriter. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified September 5, 2026. No vendor pays for placement.
Why does Kalepa earn an A on AI centrality where Federato earns a B?
The removal test separates them. Strip the models from Kalepa and the screen is empty, since the structured read of a messy submission, the cross reference against external data and the priority score against appetite are all model output and no system of record sits beneath supplying anything. Strip them from Federato and a unified underwriting workflow with portfolio visibility survives, which the platform's own account of its value supports: it describes itself as consolidating analytics, scoring and workflow that underwriters previously stitched together from several vendors. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified September 5, 2026. No vendor pays for placement.
How do their implementations compare?
Federato states eight to twelve weeks and reaches native integrations with the three dominant policy administration platforms, spanning submission intake through pricing, quoting, documentation and referral workflow to invoice, with a partner portal for brokers. Kalepa states day one with no integrations required, adding inbox, portal and policy system connections afterwards. The AI FinTech Index records Kalepa's position as a genuine commercial advantage against implementations measured in quarters and as the opposite of what integration depth measures, since no policy administration system, rating engine or integration partner is named at all.
What evidence does each publish?
Both hold A. Federato names customers at the top of the market with executives on the record, including the chief underwriting officer of a global carrier's North American arm describing the platform as the unified core system for the entire policy lifecycle, and publishes falsifiable claims of hit ratio improvements of nine to twenty four percent, alongside original research surveying 500 underwriters and executives. Kalepa names Munich Re Specialty, Bowhead and SECURA, and publishes a case study on an unnamed mid market division of a top 15 global carrier reporting time to quote down 40 percent, bind rate from 30 to 34.5 percent and appetite compliance above 95 percent with 15 percent fewer underwriters, so its names and its numbers do not attach to the same account. Graded by AI FinTech Index against the same capability axes from each vendor's own published materials, verified September 5, 2026. No vendor pays for placement.
How does the AI FinTech Index grade Federato and Kalepa?
Both are graded on the same fifteen capability axes from public sources, each grade traceable to its artifact. The index records both at A on autonomy and oversight and at A on operational evidence. It records Federato at A on integration depth and treats its published autonomy design as the reference point for that axis, while grading it B on centrality and D on model supply chain. It records Kalepa at A on centrality, C on integration depth by design, and C on data stewardship. Both hold C on governance and bias disclosure. The index publishes no composite score and declares no winner.
Related comparisons
Other published head to head assessments involving these vendors or their closest peers. The full set for this category is on the Insurance AI page.
Federato holds the lower supply chain grade of the two and one of the lowest in this index, with no public material identifying the model providers behind triage, scoring and agentic quoting, no named external data sources feeding exposure and accumulation analysis, and no subprocessor list.
The edge is specific to this category: carriers price risk on data, so which third party exposure, catastrophe or property datasets inform a recommendation is a question underwriters would ordinarily ask before trusting a number. Kalepa is C rather than D only because a United States server commitment establishes country of processing, while its ensemble engine selects models it never names.
Both are C on governance and bias disclosure against a framework that has moved faster in insurance than in most financial sectors: state regulators have adopted a model bulletin on insurer use of artificial intelligence and several states impose testing duties around unfair discrimination, with the obligation landing on the carrier, which makes vendor documentation a practical necessity for the buyer rather than a courtesy.
Neither describes testing for unfair discrimination in triage or pricing, and neither explains what evidence a carrier could hand a regulator asking how automated decisions were validated. Kalepa's exposure is more concrete, since Copilot surfaces criminal activity and pending legal actions from open web sources as underwriting exposures and its own case study names violent incidents at insured premises, importing whatever geographic patterns that data carries. Neither states whether one carrier's submissions, pricing or loss experience inform models serving a competitor, and risk selection is precisely where carriers compete.